Gotowe bibliografie tematyczne / FingerPrint Detection

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Gotowa bibliografia na temat „FingerPrint Detection”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "FingerPrint Detection"

Yogita, Verma* Prof. Bhagwati Charan Patel. "FINGERPRINT DETECTION AND RECOGNIZATION TECHNIQUES USING GABOR FILTER." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 5 (2017): 722–29. https://doi.org/10.5281/zenodo.801293.

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Fingerprints are most extensively and effectively appropriate for the proof of identity in present days. Mostly because of their uniqueness among the people, public acceptance, originality, stability through life, and their least risk of invasion. Fingerprint technology, which is basically a biometric system, is utilized to identify an individual based on their physical qualities. Fingerprint matching is the trendiest biometric method appropriate to provide authentication. Fingerprint verification is one of the most trustable biometric security system in the world of computers. In this paper w

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Chavan, Vilas A., Devidas S. Bhagat, and Ajit K. Gangawane. "Overview of bimetallic nanomaterials used for visualization of latent fingerprints on various surfaces." Problems of Forensic Sciences, no. 129 (September 8, 2022): 75–91. http://dx.doi.org/10.4467/12307483pfs.22.004.16305.

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This review focuses on the current trends in the use of doped metallic nanomaterials in forensic science for the development and detection of latent fingerprints (LFPs) on various surfaces which provide better fingerprint image quality. The advantages and important results of studies conducted on latent fingerprints detection with various doped metallic nanomaterials are critically discussed. We also glimpse on fluorescent nanoparticles that have succeeded in producing high-quality fingerprint images which lead to the extraction of all three levels of fingerprint features. A few metallic nanom

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Latha, K., and C. Manikandan. "Critical Analysis and Detection of Altered Fingerprints Using Evolutionary Computation Algorithm." Applied Mechanics and Materials 573 (June 2014): 483–88. http://dx.doi.org/10.4028/www.scientific.net/amm.573.483.

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The widespread operation of modified algorithm (National Institution of Standard Technology Fingerprint image Quality (NIFQ)) in government applications allow some persons with illegal environment by neglecting the detection of altered fingerprints. By using the fingerprint quality assessment software, it is difficult to find the altered fingerprints, since the quality of image does not degrade. This paper focuses on optimizing the modified NFIQ algorithm by implementing particle swarm optimization (PSO) based on a fingerprint identification system. It can also be helpful in improving the perf

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Mohammed, Fatima, and Samira A. Mahdi. "Detection Measurements of Some Drugs Materials in Fingerprints." NeuroQuantology 20, no. 5 (2022): 483–87. http://dx.doi.org/10.14704/nq.2022.20.5.nq22198.

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The major goal of this project is to use the Gas Chromatography–Mass Spectrometry (GC-MS) instrument to evaluate the fingerprints of illicit amphetamine. Samples of amphetamine were obtained from the Iraqi Narcotics Control Bureau. The fingerprints were examined before and after contamination with anesthetic powder. The results showed a clear difference between the spectrum of the pure fingerprint and the spectrum of the contaminated fingerprint with amphetamine. The highest peak of the drug sample was recorded at the time (6.80) minutes and Abundance 120000, and in contrast the appearance of

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Lee, Youn Kyu, Jongwook Jeong, and Dongwoo Kang. "An Effective Orchestration for Fingerprint Presentation Attack Detection." Electronics 11, no. 16 (2022): 2515. http://dx.doi.org/10.3390/electronics11162515.

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Fingerprint presentation attack detection has become significant due to a wide-spread usage of fingerprint authentication systems. Well-replicated fingerprints easily spoof the authentication systems because their captured images do not differ from those of genuine fingerprints in general. While a number of techniques have focused on fingerprint presentation attack detection, they suffer from inaccuracy in determining the liveness of fingerprints and performance degradation on unknown types of fingerprints. To address existing limitations, we present a robust fingerprint presentation attack de

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Jiang, Yujia, and Xin Liu. "Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid." Journal of Electrical and Computer Engineering 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/1539298.

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Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP) in spatial pyramid is applied to recognize fingerprint livene

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Menzel, E. Roland. "Recent Advances in Photoluminescence Detection of Fingerprints." Scientific World JOURNAL 1 (2001): 498–509. http://dx.doi.org/10.1100/tsw.2001.76.

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Photoluminescence detection of latent fingerprints has over the last quarter century brought about a new level of fingerprint detection sensitivity. The current state of the art is briefly reviewed to set the stage for upcoming new fingerprint processing strategies. These are designed for suppression of background fluorescence from articles holding latent prints, an often serious problem. The suppression of the background involves time-resolved imaging, which is dealt with from the perspective of instrumentation as well as the design of fingerprint treatment strategies. These focus on lanthani

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Almehmadi, Abdulaziz. "A Behavioral-Based Fingerprint Liveness and Willingness Detection System." Applied Sciences 12, no. 22 (2022): 11460. http://dx.doi.org/10.3390/app122211460.

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Fingerprints have been used for decades to verify the identity of an individual for various security reasons. Attackers have developed many approaches to deceive a fingerprint verification system, ranging from the sensor level, where gummy fingers are created, to gaining access to the decision-maker level, where the decision is made based on low matching criteria. Even though fingerprint sensor-level countermeasures have developed advanced metrics to detect any attempt to dupe the system, attackers still manage to outwit a fingerprint verification system. In this paper, we present the Micro-be

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Madhav, Yagnasri, Dr S. China Venkateshwarlu, and Dr V. Siva Nagaraju. "Advanced Fingerprint Alteration Detection: A Comparative Analysis of Real and Synthetic Modifications Using InceptionV3 on the SOCOFing Dataset." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51223.

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This study investigates the efficacy of fingerprint alteration detection using advanced deep learning techniques, specifically focusing on both real and synthetically altered fingerprint images. Utilizing the Sokoto Coventry Fingerprint Dataset (SOCOFing), which comprises over 55,000 fingerprint images from 600 African subjects, we employed the Google InceptionV3 model to classify real and altered images under varying degrees of alteration complexity. Our experimental results demonstrate a robust performance of the model, achieving an accuracy of 91.04% for detecting alterations with easy alte

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M., Ramesh kumari. "Detection and Rectification of Distorted Fingerprints." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 1835–41. https://doi.org/10.31142/ijtsrd18185.

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One of the open come outs in fingerprint confirmation is the lack of robustness against image quality degradation. Poor quality images result in specious and missing features, thus degrading the performance of the overall system. Therefore, it is very important for a fingerprint acknowledgement system to estimate the quality and validity of the captured fingerprint images. Also the elastic distortion of fingerprints is one of the major causes for false non match. While this problem impacts all fingerprint acknowledged applications, it is especially unsafe in negative recognition applications,

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Rozprawy doktorskie na temat "FingerPrint Detection"

Sandström, Marie. "Liveness Detection in Fingerprint Recognition Systems." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2397.

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Biometrics deals with identifying individuals with help of their biological data. Fingerprint scanning is the most common method of the biometric methods available today. The security of fingerprint scanners has however been questioned and previous studies have shown that fingerprint scanners can be fooled with artificial fingerprints, i.e. copies of real fingerprints. The fingerprint recognition systems are evolving and this study will discuss the situation of today. Two approaches have been used to find out how good fingerprint recognition systems are in distinguishing between live

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TOOSI, AMIRHOSEIN. "Feature Fusion for Fingerprint Liveness Detection." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2711594.

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For decades, fingerprints have been the most widely used biometric trait in identity recognition systems, thanks to their natural uniqueness, even in rare cases such as identical twins. Recently, we witnessed a growth in the use of fingerprint-based recognition systems in a large variety of devices and applications. This, as a consequence, increased the benefits for offenders capable of attacking these systems. One of the main issues with the current fingerprint authentication systems is that, even though they are quite accurate in terms of identity verification, they can be easily spoo

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GHIANI, LUCA. "Textural features for fingerprint liveness detection." Doctoral thesis, Università degli Studi di Cagliari, 2015. http://hdl.handle.net/11584/266594.

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The main topic ofmy research during these three years concerned biometrics and in particular the Fingerprint Liveness Detection (FLD), namely the recognition of fake fingerprints. Fingerprints spoofing is a topical issue as evidenced by the release of the latest iPhone and Samsung Galaxy models with an embedded fingerprint reader as an alternative to passwords. Several videos posted on YouTube show how to violate these devices by using fake fingerprints which demonstrated how the problemof vulnerability to spoofing constitutes a threat to the existing fingerprint recognition systems. De

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Ström, Bartunek Josef. "FINGERPRINT IMAGE ENHANCEMENT, SEGMENTATION AND MINUTIAE DETECTION." Doctoral thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-11149.

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Prior to 1960's, the fingerprint analysis was carried out manually by human experts and for forensic purposes only. Automated fingerprint identification systems (AFIS) have been developed during the last 50 years. The success of AFIS resulted in that its use expanded beyond forensic applications and became common also in civilian applications. Mobile phones and computers equipped with fingerprint sensing devices for fingerprint-based user identification are common today. Despite the intense development efforts, a major problem in automatic fingerprint identification is to acquire reliable matc

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Butler, Joseph G. "Automated Fingertip Detection." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3164.

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One of the oldest biometrics that has been used to uniquely identify a person is their fingerprint. Recent developments in research on fingerprint collection have made it possible to collect fingerprint data from a stand-off digital image. Each of the techniques developed so far have relied on either a very controlled capture environment to ensure only a single fingertip is collected or manual cropping of the image down to the fingertip. The main body of the research focuses on extracting the fingerprint itself. If fingerprint collection via digital image is ever to be fielded in the real worl

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Memon, Shahzad Ahmed. "Novel active sweat pores based liveness detection techniques for fingerprint biometrics." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7060.

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Liveness detection in automatic fingerprint identification systems (AFIS) is an issue which still prevents its use in many unsupervised security applications. In the last decade, various hardware and software solutions for the detection of liveness from fingerprints have been proposed by academic research groups. However, the proposed methods have not yet been practically implemented with existing AFIS. A large amount of research is needed before commercial AFIS can be implemented. In this research, novel active pore based liveness detection methods were proposed for AFIS. These novel methods

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Canhoto, Olinda. "Applications of volatile fingerprint sensor arrays for rapid detection of environmental contaminants." Thesis, Cranfield University, 2005. http://hdl.handle.net/1826/919.

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The electronic nose (e-nose) technology has rapidly evolved in the past decade with a range of applications in the food industry, medical diagnosis, and recently environmental monitoring. This is the first time that this technology has been examined in detail for a range of specific environmental applications including: detection of low concentrations of bacterial, fungal and heavy metal contaminants in potable water; analyses of changes in the microbial activity of soil samples amended with heavy metals; and the detection of fungal contaminants in paper samples from library material. In some

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Nilsson, Erik. "Abstract Syntax Tree Analysis for Plagiarism Detection." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-80888.

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Today, universities rely heavily on systems for detecting plagiarism in students’essays and reports. Code submissions however require specific tools. A numberof approaches to finding plagiarisms in code have already been tried, includingtechniques based on comparing textual transformations of code, token strings,parse trees and graph representations. In this master’s thesis, a new system, cojac,is presented which combines textual, tree and graph techniques to detect a broadspectrum of plagiarism attempts. The system finds plagiarisms in C, C++ and Adasource files. This thesis discusses the met

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Nogueira, Rodrigo Frassetto 1986. "Software based fingerprint liveness detection = Detecção de vivacidade de impressões digitais baseada em software." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259824.

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Orientador: Roberto de Alencar Lotufo Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação Made available in DSpace on 2018-08-26T03:01:45Z (GMT). No. of bitstreams: 1 Nogueira_RodrigoFrassetto_M.pdf: 3122263 bytes, checksum: e6333eb55b8b4830e318721882159cd1 (MD5) Previous issue date: 2014 Resumo: Com o uso crescente de sistemas de autenticação por biometria nos últimos anos, a detecção de impressões digitais falsas tem se tornado cada vez mais importante. Neste trabalho, nós implementamos e comparamos várias técnicas baseadas

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Born, Kenton P. "Combating client fingerprinting through the real-time detection and analysis of tailored web content." Diss., Kansas State University, 2012. http://hdl.handle.net/2097/13277.

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Doctor of Philosophy Department of Computing Science David Gustafson The web is no longer composed of static resources. Technology and demand have driven the web towards a complex, dynamic model that tailors content toward specific client fingerprints. Servers now commonly modify responses based on the browser, operating system, or location of the connecting client. While this information may be used for legitimate purposes, malicious adversaries can also use this information to deliver misinformation or tailored exploits. Currently, there are no tools that allow a user to detect when

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Książki na temat "FingerPrint Detection"

Hardwick, S. A. Fingerprint detection by fluorescence examination: A guide to operational implementation. Police Scientific Development Branch, Home Office, 1990.

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Menzel, E. Roland. An introduction to lasers, forensic lights, and fluorescent fingerprint detection techniques. Lightning Powder Co., 1991.

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Dr, Almog Joseph, Springer Eliot, and Mishṭeret Yiśraʼel, eds. Proceedings of the International Symposium on Fingerprint Detection and Identification, June 26-30, 1995, Neurim, Israel. Israel National Police, 1996.

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Tao, Lin. Detection of latent fingerprints on counterfeit currency. [s.n.], 1996.

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Škvorecký, Josef. Detective stories: Some notes on Fingerprints. University of Toronto Press, 1991.

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Bugeja, Michael J. The purple fingerprint. Pocket Books, 2001.

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West, Tracey. The fingerprint files. Scholastic, 2007.

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Tracey, West. The fingerprint files. Scholastic, 2007.

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Vernon, David. Automatic detection of secondary creases in finger prints. Trinity College, Department of Computer Science, 1992.

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C, Hinter Parker, and Parker Brothers, eds. The case of the chocolate fingerprints. Scholastic, 1995.

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Części książek na temat "FingerPrint Detection"

Ellingsgaard, John, and Christoph Busch. "Altered Fingerprint Detection." In Handbook of Biometrics for Forensic Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50673-9_5.

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Mainguet, Jean-François. "Fingerprint Fake Detection." In Encyclopedia of Biometrics. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_59.

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Schuckers, Stephanie A. C. "Liveness Detection: Fingerprint." In Encyclopedia of Biometrics. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_68.

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Bleay, Stephen M. "Optical detection and enhancement techniques." In Fingerprint Development Techniques. John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119187400.ch6.

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Liu, Manhua, Xudong Jiang, and Alex Chichung Kot. "Fingerprint Reference Point Detection." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_38.

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Zhang, Meng, Jianjiang Feng, and Jie Zhou. "Fingerprint Presentation Attack Detection via Analyzing Fingerprint Pairs." In Biometric Recognition. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31456-9_2.

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Johnson, Peter, and Stephanie Schuckers. "Fingerprint Spoofing and Liveness Detection." In Forensic Science. Wiley-VCH Verlag GmbH & Co. KGaA, 2016. http://dx.doi.org/10.1002/9783527693535.ch16.

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Franco, Annalisa, and Davide Maltoni. "Fingerprint Synthesis and Spoof Detection." In Advances in Biometrics. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84628-921-7_20.

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Reddy, Y. Prashanth, Kamlesh Tiwari, Vandana Dixit Kaushik, and Phalguni Gupta. "An Efficient Fingerprint Minutiae Detection Algorithm." In Communications in Computer and Information Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22915-7_18.

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Ghiani, Luca, Paolo Denti, and Gian Luca Marcialis. "Experimental Results on Fingerprint Liveness Detection." In Articulated Motion and Deformable Objects. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31567-1_21.

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Streszczenia konferencji na temat "FingerPrint Detection"

Rashmi, K. A., T. Chethana, K. S. Divya Shree, M. Divya, and Hadiya Amber. "Blood Group Detection Using Fingerprint." In 2025 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2025. https://doi.org/10.1109/ickecs65700.2025.11034795.

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Akhan, M. B. "A flexible fingerprint identification system." In European Convention on Security and Detection. IEE, 1995. http://dx.doi.org/10.1049/cp:19950513.

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Granell, Emilio, Diana Bri, Jesus Tomas, and Jaime Lloret. "Smart devices fingerprint detection." In 2012 IEEE Globecom Workshops (GC Wkshps). IEEE, 2012. http://dx.doi.org/10.1109/glocomw.2012.6477587.

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Gottschlich, Carsten, Anna Mikaelyan, Martin Aastrup Olsen, Josef Bigun, and Christoph Busch. "Improving fingerprint alteration detection." In 2015 9th International Symposium on Image and Signal Processing and Analysis (ISPA). IEEE, 2015. http://dx.doi.org/10.1109/ispa.2015.7306037.

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Fitz, A. P. "Fingerprint pre-processing on a hexagonal grid." In European Convention on Security and Detection. IEE, 1995. http://dx.doi.org/10.1049/cp:19950508.

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Plesh, Richard, Keivan Bahmani, Ganghee Jang, et al. "Fingerprint Presentation Attack Detection utilizing Time-Series, Color Fingerprint Captures." In 2019 International Conference on Biometrics (ICB). IEEE, 2019. http://dx.doi.org/10.1109/icb45273.2019.8987297.

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Arora, Shefali, Naman Maheshwari, and MPS Bhatia. "Spoofed Fingerprint Detection Based on Time Series Fingerprint Image Analysis." In 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). IEEE, 2018. http://dx.doi.org/10.1109/icsccc.2018.8703334.

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Akhtar, Zahid, Christian Micheloni, and Gian Luca Foresti. "Correlation based fingerprint liveness detection." In 2015 International Conference on Biometrics (ICB). IEEE, 2015. http://dx.doi.org/10.1109/icb.2015.7139054.

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Palka, Norbert, and Marcin Kowalski. "Terahertz detection of fingerprint spoofing." In 2020 45th International Conference on Infrared, Millimeter and Terahertz Waves (IRMMW-THz). IEEE, 2020. http://dx.doi.org/10.1109/irmmw-thz46771.2020.9370828.

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Al-Ajlan, Amani. "Survey on fingerprint liveness detection." In 2013 International Workshop on Biometrics and Forensics (IWBF 2013). IEEE, 2013. http://dx.doi.org/10.1109/iwbf.2013.6547309.

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Raporty organizacyjne na temat "FingerPrint Detection"

ASHBY, CAROL I., TIMOTHY J. SHEPODD, WILLIAM G. YELTON, and DAVID J. MURON. Rapid Ultrasensitive Chemical-Fingerprint Detection of Chemical and Biochemical Warfare Agents. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/808603.

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Paul Shnitser. Automatic hyperspectral camera for latent fingerprint detection and contrast enhancement. Final report, September 2, 1998 - March 17, 1999. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/758305.

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Irudayaraj, Joseph, Ze'ev Schmilovitch, Amos Mizrach, Giora Kritzman, and Chitrita DebRoy. Rapid detection of food borne pathogens and non-pathogens in fresh produce using FT-IRS and raman spectroscopy. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7587221.bard.

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Rapid detection of pathogens and hazardous elements in fresh fruits and vegetables after harvest requires the use of advanced sensor technology at each step in the farm-to-consumer or farm-to-processing sequence. Fourier-transform infrared (FTIR) spectroscopy and the complementary Raman spectroscopy, an advanced optical technique based on light scattering will be investigated for rapid and on-site assessment of produce safety. Paving the way toward the development of this innovative methodology, specific original objectives were to (1) identify and distinguish different serotypes of Escherichi

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Honey authenticity: collaborative data sharing feasibility study. Food Standards Agency, 2023. http://dx.doi.org/10.46756/sci.fsa.fbt231.

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According to the UN,1 there are more than 90 million managed beehives around the world producing about 1.9 million tonnes of honey worth more than £5 billion a year. That honey will then be packaged, as single origin or a blend of honey from different sources, and sold for consumption. Given the size of the market and the immense environmental benefits of beekeeping – three out of four crops depend on pollination by bees – it is an industry on which both livelihoods and lives depend. Target for adulteration As a labour-intensive, high-value expensive product with an often complex supply chain,

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